论文标题
在网络物理系统中针对FDI传感器攻击的安全融合估计
Secure Fusion Estimation Against FDI Sensor Attacks in Cyber-Physical Systems
论文作者
论文摘要
本文涉及网络物理系统的安全多传感器融合估计的问题，在该系统中，传感器测量可能会被错误的数据注入（FDI）攻击篡改。在这项工作中，人们认为对手可能无法攻击所有传感器。也就是说，几个传感器仍未受到攻击。在这种情况下，通过增强方法构建了新的本地重组子系统，包括FDI攻击信号和未攻击的传感器测量。然后，在线性最小方差感方面设计了关节的卡尔曼融合估计器，以同时估计系统状态和外国直接投资攻击信号。最后，采用说明性示例来显示所提出方法的有效性和优势。
This paper is concerned with the problem of secure multi-sensors fusion estimation for cyber-physical systems, where sensor measurements may be tampered with by false data injection (FDI) attacks. In this work, it is considered that the adversary may not be able to attack all sensors. That is, several sensors remain not being attacked. In this case, new local reorganized subsystems including the FDI attack signals and un-attacked sensor measurements are constructed by the augmentation method. Then, a joint Kalman fusion estimator is designed under linear minimum variance sense to estimate the system state and FDI attack signals simultaneously. Finally, illustrative examples are employed to show the effectiveness and advantages of the proposed methods.
